基于二次分数低阶协方差的时延估计方法

针对强脉冲噪声背景下基于分数低阶统计量时延估计方法性能退化且需要噪声先验知识的问题，提出了一种基于二次分数低阶协方差的时延估计新方法。所提方法首先利用有界非线性Sigmoid函数对含有脉冲噪声的信号进行预处理，使其在不影响有用信号时延信息的基础上对附加脉冲噪声进行充分压缩；然后对处理后的收发信号进行二次分数低阶协方差运算，即求得发射信号的自分数低阶协方差和收发信号的互分数低阶协方差之后，再次计算二者的互分数低阶协方差，以期更大程度上抑制脉冲噪声的影响。通过模拟仿真实验对所提方法进行了有效性验证，结果表明所提方法突破了分数低阶矩阶次需小于Alpha稳定分布噪声特征指数的限制，并且比分数低阶协方差方法具有更高的估计精度。仿真实验结果表明在广义信噪比-10 dB情况下，时延估计用时为0.056 0 s，准确率达到97.76%。

Time delay estimation method based on second-orderfraction low-order covariance

In the background of strong impulse noise, the performance of fractional low-order statistics delay estimation method is degraded and the prior knowledge of noise is required. In order to solve the problem, a new time delay estimation method based on second-order fractional low order covariance is proposed. Firstly, the bounded nonlinear sigmoid function is used to process the signal with impulse noise, so that the additional impulse noise can be fully compressed without affecting the time delay information carried by useful signals. Then, the second-order fractional low-order covariance operation is carried out on the processed signals of receival and transmission, that is, after obtaining the self-fractional low-order covariance of the transmitted signals and the mutual fractional low-order covariance of the received and transmitted signals, the mutual fractional low-order covariance of the two is calculated again, thus, the effect of impulse noise can be further suppressed. Finally, the effectiveness of the proposed method is verified by simulation experiments. The results show that the proposed method is free from the restriction that the fractional low-order covariance index is less than the characteristic index of Alpha stable distribution noise, and has higher estimation accuracy than the fractional low-order covariance method. The simulation experiment results show that under the generalized signal-to-noise ratio of -10 dB, the delay estimation takes 0.056 0 s and the accuracy reaches 97.76%.